Cognitive Radio (CR) is a radio communications and networking technology that has recently attracted considerable interest from academia as well as industry worldwide. It follows the design philosophy of Dynamic Spectrum Access (DSA) as opposed to a fixed spectrum allocation policy. The enabling technology for CR is spectrum sensing, which is the inference of presence/absence of primary users (...

An absolute distance measurement sensor based on self-mixing interferometry (SMI) is suitable for application in aerospace due to its small size and light weight. However, an SMI signal with a high sampling rate places burden devices other onboard sources. using compressed sensing (CS) proposed this work relieve burden. The was sampled via matrix at lower than Nyquist’s law then recovered by th...

The mathematical theory of compressed sensing (CS) asserts that one can acquire signals from measurements whose rate is much lower than the total bandwidth. Whereas the CS theory is now well developed, challenges concerning hardware implementations of CS-based acquisition devices--especially in optics--have only started being addressed. This paper presents an implementation of compressive sensi...

The principle of compressed sensing (CS) can be applied in a cryptosystem by providing the notion of security. In this paper, we study the computational security of a CS-based cryptosystem that encrypts a plaintext with a partial unitary sensing matrix embedding a secret keystream. The keystream is obtained by a keystream generator of stream ciphers, where the initial seed becomes the secret ke...

This paper presents a simple yet very effective timedomain sparse representation and the associated sparse recovery techniques that can robustly capture raw ultra-wideband (UWB) synthetic aperture radar (SAR) records. Unlike previous approaches in compressed sensing for SAR, we take advantage of the sparsity and the correlation directly in the raw received pulses before even attempting image fo...

It is of great significance to construct deterministic measurement matrices with good practical characteristics in Compressed Sensing (CS), including reconstruction performance, low memory cost and computing resources. Low-density-parity check (LDPC) codes CS can be closely related. This paper presents a method constructing compressed sensing based on quasi-cyclic (QC) LDPC arithmetic sequence ...

In this paper, we propose a new compression method for electroencephalographic signals based on the concept of compressed sensing (CS) for the P300 detection spelling paradigm. The method uses a universal mega-dictionary which has been found not to be patient-specific. To validate the proposed method, electroencephalography recordings from the competition for Spelling, BCI Competition III Chall...

In SAR tomography, the vertical reflectivity function for every azimuth-range pixel is usually recovered by processing data collected using a defined repeat-pass acquisition geometry. A common and appealing approach is to generate a synthetic aperture in the elevation direction through imaging from parallel tracks. However, the quality of conventional reconstruction methods is generally dictate...

Compressed sensing (CS) is a new technique for simultaneous data sampling and compression. In this paper, we propose a novel method called distributed compressed sensing for image using block measurements data fusion. Firstly, original image is divided into small blocks and each block is sampled independently using the same measurement operator, to obtain the smaller encoded sparser coefficient...